
REGISTRATION & LIGHT BREAKFAST

Conversation & Drinks
DEEP LEARNING FOR MOBILE DEVICES
Deep Learning & Healthcare In Practice


Brendan Frey - Co-Founder & CEO, & Professor - Deep Genomics & University of Toronto
Keynote: Why Genomic Medicine Needs Deep Learning
Brendan Frey - Deep Genomics & University of Toronto
How Deep Learning is Transforming Drug Discovery
Brendan Frey, CEO and Founder of Deep Genomics, will explain how AI did most of the heavy lifting in obtaining the company's first therapeutic candidate. This included discovering novel biology, designing novel compounds, prioritizing compounds by predicted potency and toxicity, creating animal models, designing animal studies and designing the clinical trial. Their AI technology is enabling Deep Genomics to explore an expanding universe of genetic therapies, and to advance novel drug candidates more rapidly and with a higher rate of success than was previously possible.




Alejandro Jaimes - CTO & Chief Scientist - Acesio
Artificial Intelligence in Improving Health Outcomes and De-Risking Clinical Trials
Alejandro Jaimes - Acesio
Alejandro (Alex) Jaimes is CTO & Chief Scientist at Acesio. Acesio focuses on Big Data for predictive analytics in Healthcare to tackle disease at worldwide scale, impacting individuals and entire populations. We use Artificial Intelligence to collect and analyze vast quantities of data to track and predict disease in ways that have never been done before- leveraging environmental variables, population movements, sensor data, and the web. Prior to joining Acesio, Alex was CTO at AiCure and prior to that he was Director of Research/Video Product at Yahoo where he led research and contributions to Yahoo's video products, managing teams of scientists and engineers in New York City, Sunnyvale, Bangalore, and Barcelona. His work focuses on Machine Learning, mixing qualitative and quantitative methods to gain insights on user behavior for product innovation. He has published widely in the top-tier conferences (KDD, WWW, RecSys, CVPR, ACM Multimedia, etc), has been a visiting professor (KAIST), and is a frequent speaker at international academic and industry events. He is a scientist and innovator with 15+ years of international experience in research leading to product impact (Yahoo, KAIST, Telefonica, IDIAP-EPFL, Fuji Xerox, IBM, Siemens, and AT&T Bell Labs). He has worked in the USA, Japan, Chile, Switzerland, Spain, and South Korea, and holds a Ph.D. from Columbia University.


AI IN DRUG DEVELOPMENT & CLINICAL TRIALS


Michael Nova - Chief Innovation Officer - Pathway Genomics
Mobile Cognitive Healthcare, Deep Learning, and Artificial Intelligence
Michael Nova - Pathway Genomics
Mobile Cognitive Healthcare, Deep Learning, and Artificial Intelligence
Every two years, the world’s database information doubles, and every three years medical information also doubles. By 2020, global healthcare data will double every three days, with 80% of the data being unstructured, or not in tabular form. To truly personalize medicine, this healthcare data needs to translate into accurate and actionable recommendations for both patients and physicians.
OME™ is a mobile consumer general health and wellness application that uses a Pathway A.I. and Cognitive Computing (IBM Watson), linked with genetic testing and other personal user information. OME™ collects and manages any type of personal health data (genetic tests, lab data, or wearable information) and dynamically delivers important personalized information to the user or physician.
Dr. Nova is currently the Chief Innovation Officer of Pathway Genomics, and was a founding team member of the company. He is the inventor of the Pathway-IBM/Watson Deep Machine Learning and Artificial Intelligence mobile application: Panorama/OME. His scientific career began as a research associate at the Salk Institute in the laboratory of Nobel Laureate Roger Guillemin. Michael was previously the founder and CEO of Discovery Partners Inc. (Nasdaq: DPII), which completed a successful $150M IPO. Dr. Nova is also the 2005 World Economic Forum (WEF) Technology Pioneer Award Winner; and the physician of record on the first person to ever have their entire genome sequenced by Illumina (2009). He is a member of the IBM Watson, Metagenics, and Salk Institute NeuroAI Advisory Boards.




Ben Glocker - Lecturer, Medical Image Computing - Imperial College London
Deep Learning for Semantic Understanding of Medical Images
Ben Glocker - Imperial College London
Deep Learning in Medical Imaging - Successes and Challenges
Machines capable of analysing and interpreting medical scans with super-human performance are within reach. Deep learning, in particular, has emerged as a promising tool in our work on automatically detecting brain damage. But getting from the lab into clinical practice comes with great challenges. How do we know when the machine gets it wrong? Can we predict failure, and can we make the machine robust to changes in the clinical data? We will discuss some of our most recent work that aims to address these critical issues and demonstrate our latest results on deep learning for analysing medical scans.
Ben Glocker is Senior Lecturer in Medical Image Computing at the Department of Computing at Imperial College London, and one of three academics leading the Biomedical Image Analysis Group. He also leads the HeartFlow-Imperial Research Team and is scientific advisor for London-based start-up Kheiron Medical Technologies. His research is at the intersection of medical image analysis and artificial intelligence aiming to build computational tools for improving diagnosis, therapy and intervention. He has received several awards including a Philips Impact Award and the Francois Erbsmann Prize. He is a member of the Young Scientists Community of the World Economic Forum. His ERC Starting Grant MIRA is devoted to developing the next generation machine intelligence for medical image representation and analysis.




Daniel McDuff - Director of Research - Affectiva
Turning Everyday Devices into Health Sensors
Daniel McDuff - Affectiva
Turning Everyday Devices into Health Sensors
Today's electronics have very sensitive optical and motion sensors. These can captures subtle signals resulting from cardiorespiratory activity. I will present how webcam(s) can be used to measure important physiological parameters without contact with the body. In addition, I will show how an ordinary smartphones can be turned into a continuous physiological monitors. Both of these techniques reveal the surprising power of devices with around us all the time. I will show how deep learning are helping us create highly scalable and low-cost applications based on these sensor measurements.
Daniel McDuff is Principal Research Scientist at Affectiva. He is building and utilizing scalable computer vision and machine learning tools to enable the automated recognition and analysis of emotions and physiology. At Affectiva Daniel is building state-of-the-art facial expression recognition software and leading analysis of the world's largest database of human emotions (currently with 8B+ data points). Daniel completed his PhD in the Affective Computing Group at the MIT Media Lab in 2014 and has a B.A. and Masters from Cambridge University. His work has received nominations and awards from Popular Science magazine as one of the top inventions in 2011, South-by-South-West Interactive (SXSWi), The Webby Awards, ESOMAR and the Center for Integrated Medicine and Innovative Technology (CIMIT). His work has been reported in many publications including The Times, the New York Times, The Wall Street Journal, BBC News, New Scientist and Forbes magazine. Daniel is also a Research Affiliate at the MIT Media Lab.


DATA EFFICIENCY & PERSONALISED MEDICINE

COFFEE


Diogo Moitinho de Almeida - Senior Data Scientist - Enlitic
Deep Learning: Modular in Theory, Inflexible in Practice
Diogo Moitinho de Almeida - Enlitic
Deep Learning: Modular in Theory, Inflexible in Practice
The high-level view of deep learning is elegant: composing differentiable components together trained in an end-to-end fashion. Deep learning seems like a perfect tool for enabling novel medical imaging applications by tackling some of its unique challenges such as large and high-dimensional datasets with unorthodox structure, extremely fine signals, and massive diversity with limited data. The reality isn't that simple, and the commonly used tools greatly limit what we are capable of doing. In this talk, we will discuss some of the unique challenges to medical deep learning, what we can do about it, and how those things can result in much better models in practice.
Diogo Moitinho de Almeida is a data scientist, software engineer, and hacker. He has previously been a medalist at the International Math Olympiad ending a 13-year losing streak for the Philippines, received the top prize in the Interdisciplinary Contest in Modeling achieving the highest distinction of any team from the Western Hemisphere, and won a Kaggle competition setting a new state-of-the-art for black box identification of causality and getting the opportunity to speak at the Conference on Neural Information Processing Systems. As a lifelong learner and big fan of online education, he has taken more classes online than he has getting his undergraduate degree at the Rensselaer Polytechnic Institute. He loves all things software and enjoys contributing to open source, giving talks on things that he's built, and improving his Emacs setup.




Neil Lawrence - Recently Elected DeepMind Professor of Machine Learning - University of Cambridge/University of Sheffield
The Data Delusion: Challenges for Democratising Deep Learning
Neil Lawrence - University of Cambridge/University of Sheffield
Machine Learning systems Design
Machine learning solutions, in particular those based on deep learning methods, form an underpinning of the current revolution in “artificial intelligence” that has dominated popular press headlines and is having a significant influence on the wider tech agenda. In this talk I will give an overview of where we are now with machine learning solutions, and what challenges we face both in the near and far future. These include practical application of existing algorithms in the face of the need to explain decision-making, mechanisms for improving the quality and availability of data, dealing with large unstructured datasets.
Neil Lawrence is a Professor of Machine Learning at the University of Sheffield. His main technical research interest is machine learning through probabilistic models. He focuses on both the algorithmic side of these models and their application. He has a particular interest on applications in personalized health and applications in the developing world. Neil is well known for his work with Gaussian processes, and has proposed Gaussian process variants of many of the successful deep learning architectures. He is also an advocate of of the ideas behind “Open Data Science” and active in public awareness (see https://www.theguardian.com/profile/neil-lawrence) and community organization. He has been both program chair and general chair of the NIPS Conference.




Jackie Hunter - Chief Executive Officer - Stratified Medical
Changing the Drug Discovery Paradigm
Jackie Hunter - Stratified Medical
Changing the Drug Discovery Paradigm
The process of drug discovery and development has fundamentally remained unaltered for the last 30 years, despite the use of modern tools and technologies. A radically new approach is needed to effectively explore the opportunities provided by the wealth of biomedical data to enable the development of new and effective treatments. Stratified Medical integrates leading edge predictive analytics, visualisation tools and machine learning to enable experienced drug hunters to explore huge, highly interconnected biomedical knowledge spaces in innovative and unprecedented ways. Stratified Medical is also committed to helping the biomedical community to better access and utilise scientific data by making tools available to the community for example ferret.
Jackie Hunter is the Chief Executive Officer of Stratified Medical. Stratified Medical unites traditional pharmaceutical development methodology with Artificial Intelligence to augment the research capabilities of its drug scientists so that they can gain new insights to increase the efficiency of medicines development. Jackie has over thirty years of experience in the bioscience research sector, working across academia and industry including leading neurology and gastrointestinal drug discovery and early childhood development for GlaxoSmithKline. She founded OI Pharma Partners in 2010 to support the life science sector in harnessing the power of open innovation and most recently was chief executive of the Biotechnology and Biological Sciences Research Council. She holds a personal chair from St George's Hospital Medical School, which was awarded in recognition of her contribution to bioscience research. In 2010 she was awarded a CBE in the Queen's Birthday Honours list for Services to the Pharmaceutical Industry.



LUNCH

COFFEE
MEDICAL IMAGES
Cosima Gretton - Guy's and St Thomas' NHS Foundation Trust
Cosima is a doctor, health tech consultant and entrepreneur. She has a background in psychology and a special interest in the challenges of designing technology for use in expert domains. She is currently working with Outcomes Based Healthcare on a project funded by Innovate UK using machine learning and smartphone sensor data to passively monitor health outcomes in diabetics. She is an alumnus of the Singularity University Graduate Studies Programme and currently an Academic Foundation trainee in Psychiatry and Psychological Medicine at St Thomas’s Hospital. She is the founder of AXNS Collective, a science communication company funded by the Wellcome Trust and the Arts Council curative collaborations between artists and scientists.


Ali Parsa - Babylon Health
How Artificial Intelligence will Change the Face of Healthcare
Everyone in the world is facing differing degrees of the same issue - the accessibility and affordability of healthcare. For some, the problem is convenience, cost or speed. For others, the issue is more serious with almost 50% of the world having little access to quality healthcare. Yet, four unstoppable trends are coming together to see the creative reconstruction of medicine within the next decade. The result will be a service that is more accessible, effective and democratic, irrespective of where people live. Today, everyone has near equal access to everything that is digital. The same may soon be happening to healthcare, and these trends show why: 1 - Diagnostics is improving at double the rate of Moore’s Law 2 - Information is free and getting smarter 3 - Smartphones and “the internet of everything” will create a global channel of healthcare delivery 4 - Intervention will be unrecognisable
These four trends are melting all that is solid in medicine into air. How it will develop no one can know, but one thing is for sure; a very different model of healthcare delivery is unfolding, and it should make the future of healthcare significantly smarter and better value for everyone.
Ali is an engineer and healthcare entrepreneur, and the founder and CEO of babylon, the UK’s leading digital healthcare service. Its purpose is to democratise healthcare by putting an accessible and affordable health service into the hands of every person on earth. In order to achieve this the company is bringing together one of the largest teams of scientists, clinicians, mathematicians and engineers to focus on combining the ever-growing computing power of machines with the best medical expertise of humans to create a comprehensive, immediate and personalised health service and make it universally available. Launched in February 2015, the service now has over 600,000 registered users globally.. babylon’s home grown success has seen the company expand into Europe and Africa in 2016, with a second head office located in Rwanda. Around 120 businesses, including Citigroup, BNY Mellon, LinkedIn and leading employee benefits and health insurance providers have partnered with babylon to offer its services to UK employees. Further, the company has partnered with the NHS to make its services available to the broader UK population. Prior to Babylon, Ali founded Circle and built it within a few years to become Europe's largest partnership of clinicians, with some £200m of revenue, near 3,000 employees and a successful IPO. Earlier, Ali was the recipient of the Royal Award for the Young Entrepreneur of the year for founding his first business, V&G, and the Healthcare Entrepreneurial Achievement Award for establishing Circle. Ali was named by The Times among the 100 global people to watch, and by HSJ among the 50 most influential people in healthcare. Ali is the UK Cabinet Office Ambassador for Mutuals and has a PhD in Engineering Physics.


Alejandro Jaimes - Acesio
Alejandro (Alex) Jaimes is CTO & Chief Scientist at Acesio. Acesio focuses on Big Data for predictive analytics in Healthcare to tackle disease at worldwide scale, impacting individuals and entire populations. We use Artificial Intelligence to collect and analyze vast quantities of data to track and predict disease in ways that have never been done before- leveraging environmental variables, population movements, sensor data, and the web. Prior to joining Acesio, Alex was CTO at AiCure and prior to that he was Director of Research/Video Product at Yahoo where he led research and contributions to Yahoo's video products, managing teams of scientists and engineers in New York City, Sunnyvale, Bangalore, and Barcelona. His work focuses on Machine Learning, mixing qualitative and quantitative methods to gain insights on user behavior for product innovation. He has published widely in the top-tier conferences (KDD, WWW, RecSys, CVPR, ACM Multimedia, etc), has been a visiting professor (KAIST), and is a frequent speaker at international academic and industry events. He is a scientist and innovator with 15+ years of international experience in research leading to product impact (Yahoo, KAIST, Telefonica, IDIAP-EPFL, Fuji Xerox, IBM, Siemens, and AT&T Bell Labs). He has worked in the USA, Japan, Chile, Switzerland, Spain, and South Korea, and holds a Ph.D. from Columbia University.


Reza Khorshidi - AIG
Reza is currently the Chief Scientist at AIG (leading the company's AI research and InsurTech innovations, globally), as well as one of the co-leads of Deep Medicine program at the University of Oxford's Martin School (focused on healthcare innovation, and the use of AI in digital health ecosystems). He obtained his DPhil (i.e., PhD) in computational neuroscience and machine learning from the University of Oxford in 2010, and since then has been leading teams, researches and disruptive innovation projects in both academia and industry.


Mahiben Maruthappu - NHS England
Mahiben is a practicing doctor and Senior Fellow to the CEO of NHS England, advising on £100 billion of annual health spending, with a focus on innovation and technology. He co-founded the NHS Innovation Accelerator and the NHS Diabetes Prevention Programme. Mahiben has advised a range of organisations, from start-ups to multilaterals, including the Swiss government and the WHO. He has a strong interest in research with over 80 peer-reviewed publications and 50 academic awards. Mahiben was educated at Oxford, Cambridge and Harvard universities; he was the first person from British healthcare to be included in Forbes’ 30 under 30.


Nathan Benaich - Playfair Capital
I joined Playfair Capital in 2013 to focus on deal sourcing, due diligence, and helping our companies grow. I'm particularly interested in artificial intelligence and machine learning, infrastructure-as-a-service, mobile, and bioinformatics. I've led, originated or participated in Seed through Growth investments including Mapillary, Appear Here, Dojo, and Festicket.
Prior to Playfair, I earned an M.Phil and Ph.D in oncology as a Gates and Dr. Herchel Smith Scholar at the University of Cambridge, and a BA in biology from Williams College. I've published research focused on technologies to halt the fatal spread of cancer around the body.


Davide Morelli - BioBeats
At BioBeats, we're working on projects that help people be well, fight stress, and be more productive. In most of these projects, deep learning approaches are taken to train models that can classify, predict and illuminate behaviour from the person's body and actions. Most of our classifiers learn from smartphone sensors, but increasingly our algorithms ingest from wearable sensors such as the Microsoft Band, Apple Watch, and upcoming projects from Google and Samsung. Our approach to building machine-learning-driven applications learns from evidence-based psychosocial intervention practices in mental health, but embodies continuous cardiovascular, skin, and movement-based sensor data in order to arrive at profound but granular insight for the individual, and their care or employer circle.
Researcher and entrepreneur, Davide leads BioBeats’ engineering team as CTO. He is a specialist in the intersection between Artificial Intelligence and music, previously ran a distributed software consultancy company in Italy for ten years. His PhD in Computer Science focuses on models that discover latent variables in performance profiles.



PANEL: How will Artificial Intelligence help to Enhance and Personalise Healthcare?

LIGHT BREAKFAST

END OF SUMMIT
Ekaterina Volkova-Volkmar - Codec
Codec helps brands remain relevant to their target audiences. Our content intelligence platform combines big social data with versatile machine learning solutions to tell brands what content resonates with the audiences they want to target, all before the brand spends big on high-production content. The result is interesting content, engaged consumers and increased marketing ROI. We enable brands to start contributing to culture through more relevant, valuable and impactful content. In this talk I will describe our innovative approach to one of the foundations in our research - brand audience analysis and relevant tribe search.
Ekaterina Volkova-Volkmar is a lead data scientist at Codec. Prior to this role she was a data scientist in the field of digital health. She finished her PhD at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany, in 2014. With research background in neuroscience, computer science, and computational linguistics, Ekaterina is interested in integrating artificial intelligence into digital solutions to scale human expertise and excellence.

Alejandro Jaimes - Acesio
Alejandro (Alex) Jaimes is CTO & Chief Scientist at Acesio. Acesio focuses on Big Data for predictive analytics in Healthcare to tackle disease at worldwide scale, impacting individuals and entire populations. We use Artificial Intelligence to collect and analyze vast quantities of data to track and predict disease in ways that have never been done before- leveraging environmental variables, population movements, sensor data, and the web. Prior to joining Acesio, Alex was CTO at AiCure and prior to that he was Director of Research/Video Product at Yahoo where he led research and contributions to Yahoo's video products, managing teams of scientists and engineers in New York City, Sunnyvale, Bangalore, and Barcelona. His work focuses on Machine Learning, mixing qualitative and quantitative methods to gain insights on user behavior for product innovation. He has published widely in the top-tier conferences (KDD, WWW, RecSys, CVPR, ACM Multimedia, etc), has been a visiting professor (KAIST), and is a frequent speaker at international academic and industry events. He is a scientist and innovator with 15+ years of international experience in research leading to product impact (Yahoo, KAIST, Telefonica, IDIAP-EPFL, Fuji Xerox, IBM, Siemens, and AT&T Bell Labs). He has worked in the USA, Japan, Chile, Switzerland, Spain, and South Korea, and holds a Ph.D. from Columbia University.




Mohamed Sayed - Founder & CEO - Heuro Labs
Systemic Learning and the Data Value Chain
Mohamed Sayed - Heuro Labs
Programmable Data: Plugging AI Into Your Business Flows
We are generating world record volumes of data every day. We have always generated data, but now we can capture and transmit much more of it. However our machines still do very little to help us understand this data.As things become connected, and human-computer interfaces are changed, we need our machines to understand our data and act on them appropriately.We introduce the novel concept of programmable data and show how Heuro Labs Cognitio transforms unstructured data to primitives that anyone can program to enact intelligent behavior. We will demo applications in industrial IoT, Automotive and Healthcare.
Heuro Labs is a Berlin, based startup that developed Cognitio, a cognitive intelligence framework offered as a service or on premise with special focus on ease of use, privacy, knowledge ownership. Supporting different modalities and data sources, the service enables enterprises to maximize the data value extraction while focusing on high level semantics.
Mohamed Sayed is a technologist with over 20 years of experience working at different layers of the software stack.Most recently he played an instrumental role in building large scale distributed systems at Nokia serving up to a billion users/day handling data of different modalities and velocities. Prior to that, he was at Yahoo! where he was responsible for high trafficked services delivered through thousands of servers in more than 10 global locations. He is the recipient of Nokia Impact Award '11 and Symantec Start award '04



PANEL: Is Integrating AI into Healthcare Worth the Risks?


Ioannis Katramados - Founder - COSMONiO
Anomaly Detection in Radiological Images Using Deep Learning
Ioannis Katramados - COSMONiO
Anomaly Detection in Radiological Images Using Deep Learning
Deep learning is usually linked to Big Data. However, in a medical context radiologists often need help in diagnosing rare conditions with limited historical data. Can Deep Learning prove a useful tool in such cases? COSMONiO is designing NOUS, a deep neural network platform that aims to make high-accuracy predictions using significantly smaller training datasets generated from X-ray, CT, MRI and PET scanners. We will discuss the main challenges and how we address them.
Ioannis is an engineer with a PhD degree in real-time computer vision from Cranfield University, UK. He founded COSMONiO HEALTHLAB in 2015 with a vision to develop intelligent medical technologies based on deep learning. COSMONiO's focus is on designing NOUS, an embedded deep neural network platform that aims to make high-accuracy predictions using significantly smaller training datasets. To achieve this COSMONiO collaborates closely with UMC Groningen, one of the leading university hospitals in The Netherlands. Their research is currently focussing on performing automated anomaly detection on thoracic X-rays.


PERSONAL HEALTH ASSISTANT


Alex Matei - Digital Health Manager - Nuffield Health
Deep Learning for Digital Health
Alex Matei - Nuffield Health
Alex is a Digital Health Manager at Nuffield Health. With an academic background in Software Engineering at University College London, he is now working on embedding machine learning into health prevention and wellbeing services. Within Nuffield, he advocates personalisation and tailoring across the customer journey. To improve health outcomes, Alex is investigating how behaviour change techniques can be amplified though artificial intelligence.




Alex Zhavoronkov - CEO - Insilico Medicine
Applications of Deep Learning Methods for Aging Research & Other Areas of Healthcare
Alex Zhavoronkov - Insilico Medicine
Applications of Deep Learning Methods for Aging Research & Other Areas of Healthcare
While there is still skepticism with regard to applications of deep learning to biomarker development and drug discovery using blood biochemistry and transcriptomic data, there are multiple applications that show promise. Recently we used an ensemble of feed forward deep neural networks to build a predictor of chronological age and gender trained on a data set of 920,000 common blood biochemistry and clinical cell count data samples of 41 parameters each achieving F1 scores of roughly 0.84 with epsilon of 10 years and F1 of 0.96 for gender. The predictor is available at www.Aging.AI.
Alex Zhavoronkov, PhD, is the CEO of Insilico Medicine, CSO of the Biogerontology Research Foundation, director of the International Aging Research Portfolio (IARP), head of the regenerative medicine lab at the Center for Pediatric Hematology, Oncology and Immunology in Moscow and adjunct professor of the Moscow Institute of Physics and Technology. Previously he served as the director of ATI Technologies and CTO of NeuroG Neuroinformatics. He is the author of "The Ageless Generation: How advances in biomedicine will transform the global economy" (Palgrave Macmillan, 2013) and co-organizer of the annual Aging Research Forum at the Basel Life Science Week.


APPLICATIONS OF DEEP LEARNING
DEEP LEARNING FOR MOBILE DEVICES

LUNCH
STARTUP SESSION


Vinay Kumar Sankarapu - CEO & Co-Founder - Arya.ai
Automating Medical Imaging & Preliminary Diagnosis Using Virtual Assistants
Vinay Kumar Sankarapu - Arya.ai
Automating Medical Imaging and Preliminary Diagnosis using Virtual Assistants built on multi-functional deep learning networks.
Deep learning has been producing amazing applications in the areas of text, language, speech, images, videos & analytics. However, till now, the applications of Deep Learning always have been singular and point focused. Most of the times in medicine, the interpretations need multi-tasking. For example, while arriving at a diagnosis, a doctor has to verify and gather data sources from various formats like imaging, sensor inputs & feedback from the patient. Point based AI system limit deeper understanding of medical situations. A robot with unified multi-functional deep neural networks can cross communicate the learning and can analyze the situation better. But what are the complexities in developing such networks? What kind of frameworks might work initially? Is it possible to have a modular approach in constructing a multi functional medical assistant?
Arya.ai is a developer platform for artificial intelligence with deep learning tools in language, vision, text, speech, dialogues and reasoning. Using the modules in the platform, developers can build multi-tasking virtual systems that can be customized to a vast number of tasks. Arya.ai has been named recently in the Forbes Asia 30 under 30 list, selected for 'International Innovation awards' by Paris&co - innovation agency from Paris, & has been named as a top 4 next generation technology startup by Silicon Valley Forum. Arya.ai has been working in Deep Learning to automate the AI building process for faster adoption of this technology.
Vinay Kumar is a researcher in Nano-tech from IIT Bombay, developed prediction models in formation of nano-lenses with nano centimeter scale and that has accurately predicted with over 80% accuracy. He founded an AI platform arya.ai along with his co-founder Deekshith Marla who is a researcher in NLP from the same institute. He also authored two books when he was 20y and published them in national and international medium. He also received an excellence award for his research at 21y from ISHRAE.


Sobia Hamid - University of Cambridge
Dr Sobia Hamid recently wrote a paper for The Wilberforce Society advising policy makers on the opportunities and risks of artificial intelligence in medicine and healthcare. Sobia has been working in the area of personalised medicine and machine learning undertaking scientific and commercial due diligence and marketing for venture capital, biotech and pharma companies. Sobia completed her PhD in Epigenetics at the University of Cambridge, undertaking her research into genomic imprinting at The Babraham Institute. In 2011 Sobia founded Data Insights Cambridge, a networking community for data scientists.



Ferdinando Rodriguez y Baena - Reader in Medical Robotics - Imperial College London
Panelist
Ferdinando Rodriguez y Baena - Imperial College London
Ferdinando Rodriguez y Baena graduated with a First Class Honours degree in Mechatronics and Manufacturing Systems Engineering from King’s College London in 2000. He then joined the Department of Mechanical Engineering at Imperial College, where he gained a PhD in Medical Robotics. He is now a reader in Mechanical Engineering, where he leads the Mechatronics in Medicine Laboratory.
His past research has focused on development of intra-operative registration methods suitable for minimally invasive knee replacement surgery with a hands-on robot. His work, which was carried out in collaboration with an Imperial College spinout, the Acrobot Company ltd. (which was acquired by Stanmore Implants Worldwide in 2010, and the rights for which were sold to Mako Sugical in 2013), has been presented in over 50 journal publications and peer reviewed conferences, and contributed to the world-first robotic assisted intervention in unicompartmental knee arthroplasty. Dr Rodriguez y Baena’s current research interests lie in the application of mechatronic systems to medicine, in the specific areas of clinical training, diagnostics and surgical intervention.

Guy Gross - Imperial College Health Partners
Guy is a doctor and entrepreneur with an MBA from London Business School who joined the team in January 2015 as Innovation Delivery Lead. He is passionate about the NHS and is driven to maintain its stature as a beacon in the global health economy. His role is to help our partners by catalysing the cultural and operational changes needed to stay competitive in an increasingly modern, digital and patient-centred world, to create opportunities for collaboration and to embed best practice into care pathways.
Over the 15 years prior to joining Imperial College Health Partners he was a Senior Innovation and Growth consultant working around the World within large organisations to launch new ventures while cultivating openness to innovation within the workforce. In parallel he has run his own ventures, which include winning the £1.6m NHS contract to deliver shared-decision making tools so that patients are more involved in decisions about their care, working with the National Clinical Directors and over 300 thought leaders in the NHS.




Alejandro Vicente Grabovetsky - Co-Founder - Avalon
Detecting Dementia Before it Happens
Alejandro Vicente Grabovetsky - Avalon
Detecting Dementia Before it Happens
99.6% of clinical trials for Dementia have not worked. Drugs used today do not address the root causes but only alleviate symptoms for a few years. To discover drugs that work, pharmaceutical companies have shifted clinical trial towards earlier stage patients. However, the putative early stage of Dementia, Mild Cognitive Impairment (MCI), progresses to actual Dementia at less than 15% per year, meaning a clinical trial needs to enrol many patients and last many years to show effectiveness. We have developed algorithms that can find the patients who convert next year with an accuracy of 75%, meaning that clinical trials need fewer patients for less time, drastically decreasing cost.
Alejandro (Sasha) Vicente Grabovetsky is a Cognitive Neuroscientist specialising in memory. He graduated with a BA and a PhD from Cambridge University and did his Post-Doc at the Donders Centre for Cognitive Neuroimaging. He left academia and joined the Entrepreneur First program in London. There, he met his co-founder, livier van den Biggelaar, a Software Engineer who built complex Machine Learning systems in his PhD at the University of Brussels and in industry.




Eduardo W. Jorgensen - CEO - MedicSen
MedicSen Artificial Pancreas: Deep Learning to Improve Life Science Outcomes
Eduardo W. Jorgensen - MedicSen
Predictive Algorithms and their Impact in Chronic Diseases Management: Diabetes Case
Eduardo will share his vision on the major role that artificial intelligence can have in the digital transformation of the healthcare sector. As a medical doctor and CEO of a medical devices company, he has negotiated with major stakehoders and has clear insights about the needs of both the industry and the patient. Personalized self care, preventive diagnosis, individual treatments and patient support programs, everything available thanks to predictive models and easy interfaces.
Eduardo W. Jorgensen: 2015 UAM Bachelor in Medicine, Built several teams for medical research doing college, passionate about medicine and new technologies, specially in the area of neuroscience and perception. My goal is to change the wy we live with chronic diseases. Spanish national with great interest in medicine, neuroscience and technologies. Perfect domain of English for fluent conversations and negotiations. Had an enrollment of honor prior to college, got into medical school in 2009 and graduated in 2015. In the period, got selected for StartupsMansion (NYC entrepreneurs program), had funded two companies: Livinplans (Surprise travelling agency) and MedicSen (non invasive artificial Pancreas for diabetes) and have been accelerated by TURN8 in Dubai. At the end of the day, I try to learn as much as possible about the world and get surrounded by the top innovative people to form good multidisciplinary teams capable of disrupting every aspect.




Riley Doyle - CEO & Technical Lead - Desktop Genetics
Optimising CRISPR Genome Editing using Machine Learning
Riley Doyle - Desktop Genetics
Optimising CRISPR Genome Editing using Machine Learning
Desktop Genetics is designing and testing CRISPR experiments to create training datasets for an AI that can be used for genome engineering applications in microbe, plant, animal and human cells. Decision rules are commonly used to design CRISPR genome editing procedures. Such rules use sequence-level and contextual features of the predicted genomic cut site locations to predict the activity, specificity, and outcome of using CRISPR in vitro and in vivo. We demonstrate significant improvements in designing genome editing procedures, which we have tested in an immortalized melanoma cell line and report on here.
As a biochemist turned software engineer, Riley recognized the enormous untapped potential for software innovation in the life sciences. An alum of Genentech, he brings ten years of laboratory-based genetic engineering experience to Desktop Genetics, where his team's research is focused on software systems for the rational design of CRISPR/Cas9 Genome Editing vectors and libraries. Riley is passionate about developing the next-generation of bioinformatics tools that drive science forward. He holds a Bachelor's of Engineering from Dartmouth College, a Bachelor’s of Arts in Biochemistry from Colby College, and and an MPhil in Bioscience Enterprise from the University of Cambridge.



COFFEE


David Clifton - Associate Professor of Engineering Science - University of Oxford
Machine Learning for the Next Generation of Health Informatics
David Clifton - University of Oxford
Deep learning for healthcare technologies
With the confluence of very large datasets now becoming available in healthcare along with methods from deep learning to providing new ways of using them, healthcare is poised to adopt new tools based on such technologies in coming years. This talk describes work undertaken between the University of Oxford and the Oxford University Hospitals in developing early systems in this field.
David A. Clifton is Associate Professor of Engineering Science at the University of Oxford and leads the Computational Health Informatics (CHI) Laboratory, after having trained in information engineering at the University of Oxford. CHI Lab focusses on the interface between machine learning and healthcare, in partnership with leading clinicians from the Oxford University Hospitals NHS Trust, and has grown rapidly to over 20 members in the two years since its founding, with support from the Wellcome Trust, UK Department of Health, NHS National Institute of Health Research, Engineering & Physical Sciences Research Council, Royal Academy of Engineering, Natural Environment Research Council, and the Bill & Melinda Gates Foundation.



Matteo Berlucchi - CEO - Your.MD
AI Helps Fix Structural Issues in Global Healthcare
Matteo Berlucchi - Your.MD
Your.MD: Revolutionising pre-primary care access via chatbot
Matteo Berlucchi will delve into the process of building an artificial medical brain that is capable of finding the most likely cause of an indisposition. Through a set of intelligent algorithms, based on a doctors’ thought process, Your.MD is capable of reaching a comparable result to a doctor when given the same information - totally personalised to fit an individual's history, profile and current situation. Matteo will address the fundamental components that make this possible: a medical knowledge base, a chat-based interface, a medical AI brain and a safe platform to store individualised structural medical data.
Matteo Berlucchi is CEO at Your.MD - the world’s first Personal Health Assistant to combine Artificial Intelligence, machine learning and content from the NHS to deliver free, personalised health information to a global audience. As one of the first Internet entrepreneurs in Europe, Berlucchi has spent his career building and growing companies and services operating across the online and mobile sectors. Prior to Your.MD, Berlucchi has served as Chief Digital Officer at Northern & Shell, founder and CEO of the ‘social ebook’ platform aNobii, as well as the first live news platform on iPhone, Livestation, and Skinkers, an award-winning digital communication platform. Berlucchi has also served as an advisor to multiple individuals and businesses.


Hiba Saleem - Doctorpreneurs
Hiba is a Director at Doctorpreneurs, the global community for medical entrepreneurs designed to inspire, connect and accelerate healthcare professionals with an interest in medical innovation and technology. Doctorpreneurs aim to provide medical entrepreneurs with the insight, network and opportunities to lead innovative improvement in healthcare.
Hiba is a graduate of Imperial College Business School and is studying medicine at Imperial College London. Her current research with her team under Lord Darzi focuses on medication noncompliance and development of mAdherence solutions. She is Co-Founder of the MedTech UK platform which is currently growing as a national university network. Hiba is working on projects in healthcare policy and digital health, such as developing an engagement tool for frontline clinical staff with Innovation 4 Health and has previously supported 3M Health Care in building an application in clinical education.

